// Copyright (c) 2023 Huawei Technologies Co., Ltd
// Copyright (c) 2019, Facebook CORPORATION.
// All rights reserved.
//
// Licensed under the BSD 3-Clause License  (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include "op_plugin/AclOpsInterface.h"
#include "op_plugin/OpApiInterface.h"
#include "op_plugin/utils/op_api_common.h"

namespace op_api {
using npu_preparation = at_npu::native::OpPreparation;

at::Tensor &reciprocal_out(const at::Tensor &self, at::Tensor &result)
{
    DO_COMPATIBILITY(aclnnReciprocal, acl_op::reciprocal_out(self, result));

    auto output_size = op_infer::input_same_output_size(self);
    npu_preparation::check_tensor({self}, result, result.scalar_type(), output_size);

    EXEC_NPU_CMD(aclnnReciprocal, self, result);
    return result;
}

at::Tensor reciprocal(const at::Tensor &self)
{
    DO_COMPATIBILITY(aclnnReciprocal, acl_op::reciprocal(self));
    // calculate the output size
    auto output_size = op_infer::input_same_output_size(self);
    auto out_dtype = (isIntegralType(self.scalar_type(), true)) ? at::kFloat : self.scalar_type();
    // construct the output tensor of the NPU
    at::Tensor result = npu_preparation::apply_tensor_without_format(output_size, self.options().dtype(out_dtype));
    // calculate the output result of the NPU
    EXEC_NPU_CMD(aclnnReciprocal, self, result);
    return result;
}

at::Tensor &reciprocal_(at::Tensor &self)
{
    DO_COMPATIBILITY(aclnnInplaceReciprocal, acl_op::reciprocal_(self));
    EXEC_NPU_CMD(aclnnInplaceReciprocal, self);
    return self;
}

} // namespace op_api
